Arabidopsis GERANYLGERANYL DIPHOSPHATE SYNTHASE 11 is a hub isozyme required for the production of most photosynthesis-related isoprenoids

Autor: Peter Bühlmann, Alexander Graf, Diana Coman, Laurent Bigler, Maite Colinas, Eva Vranová, Manuel Rodríguez-Concepción, Philipp Rütimann, M. Victoria Barja, Ralf Welsch, M. Águila Ruiz-Sola, Gilles Beck, Wilhelm Gruissem

Publikováno v: Digital.CSIC: Repositorio Institucional del CSIC
Consejo Superior de Investigaciones Científicas (CSIC)
Digital.CSIC. Repositorio Institucional del CSIC
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Most plastid isoprenoids, including photosynthesis-related metabolites such as carotenoids and the side chain of chlorophylls, tocopherols (vitamin E), phylloquinones (vitamin K), and plastoquinones, derive from geranylgeranyl diphosphate (GGPP) synt

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bb53f7f82decaae201d0a2b059ee8931
http://hdl.handle.net/10261/248019

A flexible protocol for targeted gene co-expression network analysis

Autor: Diana, Coman, Philipp, Rütimann, Wilhelm, Gruissem

Publikováno v: Methods in molecular biology (Clifton, N.J.). 1153

The inference of gene co-expression networks is a valuable resource for novel hypotheses in experimental research. Routine high-throughput microarray transcript profiling experiments and the rapid development of next-generation sequencing (NGS) techn

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid________::741f6dde124868da4601966581774c4c
https://pubmed.ncbi.nlm.nih.gov/24777806

Correlated variables in regression: clustering and sparse estimation

Autor: Cun-Hui Zhang, Sara van de Geer, Peter Bühlmann, Philipp Rütimann

Publikováno v: Journal of Statistical Planning and Inference

We consider estimation in a high-dimensional linear model with strongly correlated variables. We propose to cluster the variables first and do subsequent sparse estimation such as the Lasso for cluster-representatives or the group Lasso based on the

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::95c287ab1d7892690c38576894409335
http://arxiv.org/abs/1209.5908

High dimensional sparse covariance estimation via directed acyclic graphs

Autor: Peter Bühlmann, Philipp Rütimann

Publikováno v: Electron. J. Statist. 3 (2009), 1133-1160

We present a graph-based technique for estimating sparse covariance matrices and their inverses from high-dimensional data. The method is based on learning a directed acyclic graph (DAG) and estimating parameters of a multivariate Gaussian distributi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f1eb9d463564d966f2caaf296e5e0c7d